Search results for: blockchain and smart contracts in logistics

Authors: Giuseppe Timperio, Robert De Souza

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The combination of factors such as temperamental climate change, rampant urbanization of risk exposed areas, political and social instabilities, is posing an alarming base for the further growth of number and magnitude of humanitarian crises worldwide. Given the unique features of humanitarian supply chain such as unpredictability of demand in space, time, and geography, spike in the number of requests for relief items in the first days after the calamity, uncertain state of logistics infrastructures, large volumes of unsolicited low-priority items, a proactive approach towards design of disaster response operations is needed to achieve high agility in mobilization of emergency supplies in the immediate aftermath of the event. This paper is an attempt in that direction, and it provides decision makers with crucial strategic insights for a more effective network design for disaster response. Decision sciences and ICT are integrated to analyse the robustness and resilience of a prepositioned network of emergency strategic stockpiles for a real-life case about Indonesia, one of the most vulnerable countries in Asia-Pacific, with the model being built upon a rich set of quantitative data. At this aim, a network optimization approach was implemented, with several what-if scenarios being accurately developed and tested. Findings of this study are able to support decision makers facing challenges related with disaster relief chains resilience, particularly about optimal configuration of supply chain facilities and optimal flows across the nodes, while considering the network structure from an end-to-end in-country distribution perspective.

Keywords: disaster preparedness, humanitarian logistics, network optimization, resilience

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Authors: Saeid Rabiei Majd, Motahareh Alvandi, Mehrad Rabiei

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The rapid economic and technological development of any country depends on access to cheap sources of energy. Competition for access to petroleum resources is always accompanied by numerous environmental risks. These factors have caused more attention to environmental issues and sustainable development in petroleum contracts and activities. Nowadays, a sign of developed countries is adhering to the principles and rules of international environmental law and sustainable development of commercial contracts. China has entered into play through the massive project plan, One Belt, One Road. China is becoming a new emerging power in the world. China's bilateral investment treaties have an impact on environmental rights and sustainable development through regional and international foreign direct investment. The aim of this research is to examine China's key position to promote and improve environmental principles and international law and sustainable development in the energy sector in the world through the initiative, One Belt, One Road. Based on this hypothesis, it seems that in the near future, China's investment bilateral investment treaties will become popular investment model used in global trade, especially in the field of energy and sustainable development. They will replace the European and American models. The research method is including literature review, analytical and descriptive methods.

Keywords: principles of sustainable development, oil and gas law, Chinas BITs, One Belt One Road, environmental rights

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Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

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3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

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Authors: Heesuk Seo, Yongtae Kim

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Online learning started in the 1990s, the spread of the Internet has been through the era of e-learning paradigm of online education in the era of smart learning change. Reflecting the different nature of the mobile to anywhere anytime, anywhere was also allows the form of learning, it was also available through the learning content and interaction. We are developing a cloud system, 'TLINKS CLOUD' that allows you to configure the environment of the smart learning without the need for additional infrastructure. Using the big-data analysis for e-learning contents, we provide an integrated solution for e-learning tailored to individual study.

Keywords: authority tool, big data analysis, e-learning, HTML5

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Authors: Sylvie Michel, Sylvie Gerbaix, Marc Bidan

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The COVID-19 pandemic has been a major and global disruption that has affected all supply chains on a worldwide scale. Consequently, the question posed by this communication is to understand how - in the face of such disruptions - supply chains, including their actors, management tools, and processes, react, survive, adapt, and even improve. To do so, the concepts of resilience and antifragility applied to a supply chain have been leveraged. This article proposes to perceive resilience as a step to surpass in moving towards antifragility. The research objective is to propose an analytical framework to measure and compare resilience and antifragility, with antifragility seen as a property of a system that improves when subjected to disruptions rather than merely resisting these disruptions, as is the case with resilience. A unique case study was studied - MSF logistics (France) - using a qualitative methodology. Semi-structured interviews were conducted in person and remotely in multiple phases: during and immediately after the COVID crisis (8 interviews from March 2020 to April 2021), followed by a new round from September to November 2023. A Delphi method was employed. The interviews were analyzed using coding and a thematic framework. One of the theoretical contributions is consolidating the field of supply chain resilience research by precisely characterizing the dimensions of resilience for a humanitarian supply chain (Reorganization, Collaboration mediated by IS, Humanitarian culture). In this regard, a managerial contribution of this study is providing a guide for managers to identify the four dimensions and sub-dimensions of supply chain resilience. This enables managers to focus their decisions and actions on dimensions that will enhance resilience. Most importantly, another contribution is comparing the concepts of resilience and antifragility and proposing an analytical framework for antifragility—namely, the mechanisms on which MSF logistics relied to capitalize on uncertainties, contingencies, and shocks rather than simply enduring them. For MSF Logistics, antifragility manifested through the ability to identify opportunities hidden behind the uncertainties and shocks of COVID-19, reducing vulnerability, and fostering a culture that encourages innovation and the testing of new ideas. Logistics, particularly in the humanitarian domain, must be able to adapt to environmental disruptions. In this sense, this study identifies and characterizes the dimensions of resilience implemented by humanitarian logistics. Moreover, this research goes beyond the concept of resilience to propose an analytical framework for the concept of antifragility. The organization studied emerged stronger from the COVID-19 crisis due to the mechanisms we identified, allowing us to characterize antifragility. Finally, the results show that the information system plays a key role in antifragility.

Keywords: antifragility, humanitarian supply chain, information systems, qualitative research, resilience.

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

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Authors: Debesh R. Roy

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The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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Authors: Mourad Bakouka, Abdelaziz Rabehi

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Companies need to have logistics and transportation in place that can adapt to the changing nature of construction sites. This ensures they can react quickly when needed. A study was conducted to develop a way to locate and track materials on construction sites. The system is an RFID/GPS integration that's required to pull off this feat. The study also reports how the platform has been used in construction. They found many advantages to using it, including reductions in both time and costs as well as improved management of materials orders. . For example, the time in which a project could start up was shortened from two weeks to three days with just a single digital order. As of now, the technology is still limited in its widespread adoption due largely to overall lack of awareness and difficulty connecting to it. However, as more and more companies embrace it in construction, the technology is expected to become ubiquitous. The developed platform provides contractors and construction managers with real-time information about the status of materials and work, allowing them to better manage the workflow in a project. The study sheds new light on this subject, which is essential to know. This work is becoming increasingly aware of the use of smart tools in constructing buildings.

Keywords: materials management, internet of things (IoT), radio frequency identification (RFID), construction site, supply chain management

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

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Authors: Emilienne Lardy, Eric Ballot, Mariam Lafkihi

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Efficient urban logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modelling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed, to describe extensively the kinetic and dynamic aspects of the driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Factor Analysis and a Generalized Linear Model have been established to link kinetic parameters with independent categorical contextual variables. The results include an assessment of the adjustment quality and the robustness of the models, as well as an overview of the model’s outputs.

Keywords: factor analysis, generalised linear model, real world driving data, traffic congestion, urban logistics, vehicle kinematics

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Authors: Serdal Akyüz, Halit Turan, Mehmet Öztürk

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The future security environment will have new battlefield and enemies. The boundaries of battlefield and the identity of enemies cannot be noticed easily. The politicians may not want to lose their soldiers in very risky operations. This approach will pave the way for smart machines like war robots and new drones. These machines will have the decision-making ability and act simultaneously. This ability can change the military targeting process. Military targeting process (MTP) benefits from a wide scope of lethal and non-lethal weapons to reach an intended end-state. This process is now managed by people but in the future smart machines can do it by themselves. At first sight, this development seems useful for humanity owing to decrease the casualties in war. Using robots -which can decide, detect, deliver and asses without human support- for homeland security and against terrorist has very crucial risks and threats. Besides, it can decrease the havoc but also increase the collateral damages. This paper examines the current use of smart war machines, military targeting process and presents a new approach to MTP from lethal autonomy concept's point of view.

Keywords: the autonomous weapon systems, the lethal autonomy, military targeting process (MTP)

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Authors: Wegene Demisie Jima

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Leather is a durable and flexible material used for various purposes including clothing, footwear, upholstery and gloves. However, the use of leather for smart product applications is a challenge since it is electrically insulating material. Here, we report a simple method to produce conducting glove leathers using an in-situ polymerization of pyrrole. The concentrations of pyrrole, ferric chloride and anthraquinone-2-sulfonic acid sodium salt monohydrate were optimized to produce maximum conductivity in the treated leathers. The coating of polypyrrole in the treated leathers was probed using FT-IR, X-ray diffraction and electron microscopic analysis. FTIR confirms that the formation of polypyrrole on the leather surface as well as presence of prominent N-C stretching band. X-ray diffraction analysis suggests para-crystallinity in the PPy-treated leathers.We further demonstrate that the treated leathers, with maximum conductivity of 7.4 S/cm, can be used for making conductive gloves for operating touch-screen devices apart from other smart product applications.

Keywords: electrical conductivity, in-situ polymerization, pyrrole, smart product

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Authors: Ismail Bile Hassan, Masrah Azrifah Azmi Murad

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This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens’ behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens’ new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework.

Keywords: unified theory of acceptance and use of technology (UTAUT) model, UTAUT2 model, smart national identity card (SNIC), health information application, privacy calculus model (PCM)

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Authors: Süleyman Günes

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The crucial effects of the COVID-19 pandemic have on social and economic systems in Turkey as well as all over the world. It has impacted logistic providers and worldwide supply chains. Unexpected risks played a central role in creating vulnerabilities for logistics service operations during the pandemic terms. This study aims to research and design qualitative and quantitive contributions to logistic services. The COVID-19 pandemic brought unavoidable risks to the logistics industry in Turkey. The Logistic Service Providers (LSPs) have learned how to ensure uncertainties and risks triggered by main and adverse effects. The risks that LSPs encounter during the COVID-19 pandemic have been investigated and unveiled, and identified uncertainties and risks. The cause-effect structures were displayed by the qualitative and quantitive studies. The results suggest that supply chains and demand changes triggered by the COVID-19 pandemic while it influenced financial failure and forecast horizon with operational performances.

Keywords: logistic service providers, COVID-19, development, financial failure

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: M. R. Ebrahimi, B. Mahdaviani

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Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.

Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system

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Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

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Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

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Authors: Vandenbroucke Karel, Georges Annabel, Schuurman Dimitri

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In the past years, bundling of transport flows, whether or not implemented in an intermodal process, has popped up as a promising concept in the logistics sector. Bundling of transport flows is a process where two or more shippers decide to synergize their shipped goods over a common transport lane. Promoted by the European Commission, several programs have been set up and have shown their benefits. Bundling promises both shippers and logistics service providers economic, societal and ecological benefits. By bundling transport flows and thus reducing truck (or other carrier) capacity, the problems of driver shortage, increased fuel prices, mileage charges and restricted hours of service on the road are solved. In theory, the advantages of bundled transport exceed the drawbacks, however, in practice adoption among shippers remains low. In fact, bundling is mentioned as a disruptive process in the rather traditional logistics sector. In this context, a Belgian company asked iMinds Living Labs to set up a Living Lab research project with the goal to investigate how the uptake of bundling transport flows can be accelerated and to check whether an online data sharing platform can overcome the adoption barriers. The Living Lab research was conducted in 2016 and combined quantitative and qualitative end-user and market research. Concretely, extensive desk research was conducted and combined with insights from expert interviews with four consultants active in the Belgian logistics sector and in-depth interviews with logistics professionals working for shippers (N=10) and LSP’s (N=3). In the article, we present findings which show that there are several factors slowing down the uptake of bundling transport flows. Shippers are hesitant to change how they currently work and they are hesitant to work together with other shippers. Moreover, several practical challenges impede shippers to work together. We also present some opportunities that can accelerate the adoption of bundling of transport flows. First, it seems that there is not enough support coming from governmental and commercial organizations. Secondly, there is the chicken and the egg problem: too few interested parties will lead to no or very few matching lanes. Shippers are therefore reluctant to partake in these projects because the benefits have not yet been proven. Thirdly, the incentive is not big enough for shippers. Road transport organized by the shipper individually is still seen as the easiest and cheapest solution. A solution for the abovementioned challenges might be found in the online data sharing platform of the Belgian company. The added value of this platform is showing shippers possible matching lanes, without the shippers having to invest time in negotiating and networking with other shippers and running the risk of not finding a match. The interviewed shippers and experts indicated that the online data sharing platform is a very promising concept which could accelerate the uptake of bundling of transport flows.

Keywords: adoption barriers, bundling of transport, shippers, transport optimization

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Authors: Nattida Wannaruk, Wasawat Nakkiew

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This research aims to study the factors that affect the performance of green supply chain management in the Lampang ceramics industry. The data investigation of this research was questionnaires which were gathered from 20 factories in the Lampang ceramics industry. The research factors are divided into five major groups which are green design, green purchasing, green manufacturing, green logistics and reverse logistics. The questionnaire has consisted of four parts that related to factors green supply chain management and general information of the Lampang ceramics industry. Then, the data were analyzed using descriptive statistic and priority of each factor by using the analytic hierarchy process (AHP). The understanding of factors affecting the green supply chain management of Lampang ceramics industry was indicated in the summary result along with each factor weight. The result of this research could be contributed to the development of indicators or performance evaluation in the future.

Keywords: Lampang ceramics industry, green supply chain management, analysis hierarchy process (AHP), factors affecting

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Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: E. Behmanesh, J. Pannek

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The distribution-allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution-allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near-optimal solutions particularly for large scales test problems. This paper, presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a novelty in population presentation. To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as a comparison basis for small size problems. In large size cases that we are dealing with in the real world, the Genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm.

Keywords: integrated logistics network, flexible path, memetic algorithm, genetic algorithm

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Authors: Safwan Mawlood Hussien

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Internet of Things (IoT) is a promising technology has received considerable attention in different fields such as health, industry, defence, and agro, etc. Due to the limitation capacity of computing, storage, and communication, IoT objects are more vulnerable to attacks. Many solutions have been proposed to solve security issues, such as key management using symmetric-key ciphers. This study provides a scalable group distribution key management based on ECcryptography; with less transmitted messages The method has been validated through simulations in OMNeT++.

Keywords: elliptic curves, Diffie–Hellman, discrete logarithm problem, secure key exchange, WSN security, IoT security, smart-agro

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Ihaddadene Thanina, Haraoubia Imane, Baouni Tahar

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Urban mobility is one of the first challenges of cities; it is becoming more and more problematic because it is perceived as the cause of many dysfunctions; it is not only to facilitate accessibility but also to ensure vast benefits. For this reason, several cities in the world have thought about alternatives to smart mobility and sustainable transport. Today, the sustainable city has many cards at its disposal, and a new mode is entering the urban scene: aerial cable transport; it has imposed itself as an effective mode of public transport and a real solution for the future. This electric mobility brings a new dimension, not only to collective daily travel but also to the urban space. It has an excellent capacity to redevelop the public space; it is a catalyst that allows one to appreciate the view from the sky and to discover different large-scale projects that bring an important attractiveness to the city. With regard to the cities in the world which use these systems of transport: Algeria does not escape this reality; it is the country which has the greatest number of devices of urban transport by cable in the world, with installations in many cities such as Tlemcen, Constantine, Blida, Oran, Tizi-Ouzou, Annaba, Skikda. The following study explores the role of cable transport in the transformation of the city of Algiers into a smart city. The methodology used in this work is based on the development of a set of indicators using a questionnaire survey. The main objective of this work is to shed light on cable transport as a key issue in designing the sustainable city of tomorrow, to evaluate its role in the city of Algiers, and its ability to integrate into the urban transport network.

Keywords: Algiers, cable transport, indicators, smart city

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Authors: A. Ravinder Nath, D. Jaya Prakash, T. Venkateshwarlu, P. Raja Rao

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The introduction of novel practices in research and innovation management at the university are likely to make a real difference in improving the quality of life and boost the global competitiveness for sustainable economic growth. Establishment a specific institutional structure at the university level provides professional management and administrative expertise to the university’s research community by sourcing out funding opportunities, extending guidance in grant proposal preparation and submission and also assisting in the post award reporting and regulatory observance. In addition to these it can involve in negotiating fair and equitable research contracts. Further it administer research governance to provide support and encourage collaborations across all disciplines of the university with industry, government, community based organizations, foundations, and associations at the local, regional, national and international levels/scales. The partnerships in research and innovation are more powerful and far needed tools for knowledge-based economy, where the universities can offer the services of much wanted human resources to promote, foster, and sustain excellence in research. In addition to this the institutes provide amply desired infrastructure and expertise to work with the investigators, and the industry will generate required financial resources in a coordinated manner. Further it is possible to carryout high-end applied research and synergizes the research capabilities and professional skills of students, faculty, scientists, and industrial work force.

Keywords: collaborations, competitiveness, contracts, governance

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Authors: Noor Suhaida Kasri

Abstract:

In the last three decades, Malaysia has developed fundamental legal and regulatory structures that aim to accommodate and facilitate the growth of Islamic banking and finance industry. Important building blocks have been put in place, to cite a few, the elevation of the position of the Malaysian Central Bank Shariah Advisory Council (SAC) as the apex advisory body and the empowerment of their Shariah resolutions through the Central Bank Act 1958; the promulgation of the Islamic Financial Services Act 2013 that regulate and govern Islamic finance market with a robust statutory requirement of Shariah governance and Shariah compliance. Notwithstanding these achievements, enforceability of Shariah-compliant contract remains a contentious subject. The validity of Al Bai Bithaman Ajil concept that was commonly used by the Islamic financial institutions in their financing facilities structures and documentation has been unabatedly challenged by the customers in courts. The challenge was due to the manner in which the Al Bai Bithaman Ajil transactions were carried out. Due to this legal challenge, Al Bai Bithaman Ajil financing structure seems to no longer be the practitioners’ favourite in Malaysia, though its substitute tawarruq and commodity murabahah financing structure may potentially face similar legal challenges. This paper examines the legal challenges affecting the enforceability of these underlying Shariah contracts. The examination of these cases highlights the manner in which these contracts were being implemented and applied by the Malaysian Islamic financial institutions that triggered Shariah and legal concern. The analysis also highlights the approach adopted by the Malaysian courts in determining the Shariah issues as well as the SAC in ascertaining the rulings on the Shariah issues referred to it by the courts. The paper adopts a qualitative research methodology by using textual and documentary analysis approach. The outcome of this study underlines factors that require consideration by industry stakeholder in order to ameliorate the efficacy of the existing building blocks that would eventually strengthens the validity and enforceability of Shariah-compliant contracts. This, in the long run, will further reinforce financial stability and trust into the Islamic banking and finance industry in Malaysia.

Keywords: enforceability of Shariah compliant contract, legal challenge, legal and regulatory framework, Shariah Advisory Council

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Authors: Fikiru Temesgen Gelata

Abstract:

Food security, adaptation, and climate change mitigation are all problems that can be resolved simultaneously with Climate-Smart Agriculture (CSA). This study examines determinants of climate-smart agriculture (CSA) practices among smallholder farmers, aiming to understand the factors guiding adoption decisions and evaluate the impact of CSA on smallholder farmer income in the study areas. For this study, three-stage sampling techniques were applied to select 230 smallholders randomly. Mann-Kendal test and multinomial endogenous switching regression model were used to analyze trends of decrease or increase within long-term temporal data and the impact of CSA on the smallholder farmer income, respectively. Findings revealed education level, household size, land ownership, off-farm income, climate information, and contact with extension agents found to be highly adopted CSA practices. On the contrary, erosion exerted a detrimental impact on all the agricultural practices examined within the study region. Various factors such as farming methods, the size of farms, proximity to irrigated farmlands, availability of extension services, distance to market hubs, and access to weather forecasts were recognized as key determinants influencing the adoption of CSA practices. The multinomial endogenous switching regression model (MESR) revealed that joint adoption of crop rotation and soil and water conservation practices significantly increased farm income by 1,107,245 ETB. The study recommends that counties and governments should prioritize addressing climate change in their development agendas to increase the adoption of climate-smart farming techniques.

Keywords: climate-smart practices, food security, Oincome, MERM, Ethiopia

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Authors: Mohammed Agbali, Claudia Trillo, Yusuf Arayici, Terrence Fernando

Abstract:

The wide-spread adoption of the Smart City concept has introduced a new era of computing paradigm with opportunities for city administrators and stakeholders in various sectors to re-think the concept of urbanization and development of healthy cities. With the world population rapidly becoming urban-centric especially amongst the emerging economies, social innovation will assist greatly in deploying emerging technologies to address the development challenges in core sectors of the future cities. In this context, sustainable health-care delivery and improved quality of life of the people is considered at the heart of the healthy city agenda. This paper examines the Boston innovation landscape from the perspective of smart services and innovation ecosystem for sustainable development, especially in transportation and healthcare. It investigates the policy implementation process of the Healthy City agenda and eHealth economy innovation based on the experience of Massachusetts’s City of Boston initiatives. For this purpose, three emerging areas are emphasized, namely the eHealth concept, the innovation hubs, and the emerging technologies that drive innovation. This was carried out through empirical analysis on results of public sector and industry-wide interviews/survey about Boston’s current initiatives and the enabling environment. The paper highlights few potential research directions for service integration and social innovation for deploying emerging technologies in the healthy city agenda. The study therefore suggests the need to prioritize social innovation as an overarching strategy to build sustainable Smart Cities in order to avoid technology lock-in. Finally, it concludes that the Boston example of innovation economy is unique in view of the existing platforms for innovation and proper understanding of its dynamics, which is imperative in building smart and healthy cities where quality of life of the citizenry can be improved.

Keywords: computing paradigm, emerging technologies, equitable healthcare, healthy cities, open data, smart city, social innovation

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Authors: Mehdi Attia, Sana Ben Fadhel, Lamjed Bettaieb

Abstract:

Mobile technology has become a part of our daily lives and assist learners (despite their level and age) in their leaning process using various apparatus and mobile devices (laptop, tablets, etc.). This paper presents a new learning framework based on tablets. This solution has been developed and tested in ESPRIT “Ecole Supérieure Privée d’Igénieurie et de Technologies”, a Tunisian school of engineering. This application is named ESSF: Esprit Smart School Framework. In this work, the main features of the proposed solution are listed, particularly its impact on the learners’ evaluation process. Learner’s assessment has always been a critical component of the learning process as it measures students’ knowledge. However, traditional evaluation methods in which the learner is evaluated once or twice each year cannot reflect his real level. This is why a continuous assessment (CA) process becomes necessary. In this context we have proved that ESSF offers many important features that enhance and facilitate the implementation of the CA process.

Keywords: continuous assessment, mobile learning, tablet based learning, smart school, ESSF

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Authors: Rodrigo Buaiz Boabaid

Abstract:

Tokenization of Blue Bonds is an emerging Green Finance tool that has the potential to scale Blue Carbon Projects to fight climate change. This innovative solution has a huge potential to democratize the green finance market and catalyze innovations in the climate change finance sector. Switzerland has emerged as a leader in the Green Finance space and is well-positioned to drive the adoption of Tokenization of Blue & Green Bonds. This unique approach has the potential to unlock new sources of capital and enable global investors to participate in the financing of sustainable blue carbon projects. By leveraging the power of blockchain technology, Tokenization of Blue Bonds can provide greater transparency, efficiency, and security in the investment process, while also reducing transaction costs. Investments are in line with the highest regulations and designed according to the stringent legal framework and compliance standards set by Switzerland. The potential benefits of Tokenization of Blue Bonds are significant and could transform the way that sustainable projects are financed. By unlocking new sources of capital, this approach has the potential to accelerate the deployment of Blue Carbon projects and create new opportunities for investors to participate in the fight against climate change.

Keywords: blue carbon, blue bonds, green finance, Tokenization, blockchain solutions

Procedia PDF Downloads 67